Customer Value Analytics Telecom : Data Science - (6-8 yrs)
Analytics opportunity with one of the top 10 analytics firms at their client site Abu Dhabi in their Customer Value Analytics team for individual with hands on experience in customer life cycle concept, Descriptive & Prescriptive analytics in Telecom space.
Expertise in building machine learning models like clustering, regression, random forest techniques and programming on structured / unstructured data using Python / R.
Gurgaon; Client Location Abu Dhabi
YOUR FUTURE EMPLOYER
A leading, global firm with a distinguished client providing extensive financial and asset management services.
Extensively working on wide range of data analysis, machine learning and statistical modeling algorithms and methods to solve business problems in the area of Marketing analytics
Performing advanced quantitative and statistical analysis of large datasets to identify trends, patterns, and correlations that can be used to improve business performance.
Working on machine learning techniques like Clustering, Regression, Random forest working extensively on Python.
M.S. or Ph.D. in Statistics, Engineering, Computer Science, Mathematics, Economics or related quantitative field from good B-
schools having relevant experience of 3+ yrs. in developing predictive models, forecasting models and / or machine learning algorithms in a global banking set up.
Hands-on experience with a wide variety of predictive modeling, machine learning, data mining, time series forecasting and optimization algorithms
Must have with 4+ years of experience with demonstrated ability to code complex programs in SQL and Machine Learning techniques like Python
Knowledge in Big data concepts and Hadoop would be good to have.
Highly motivated individual with good analytical skills and excellent communication skills.
WHAT IS IN STORE FOR YOU
Liaise extensively with stakeholders.
Work in a dynamic environment for an established brand.
Reach me :
Please share your CV on nikitasharma crescendogroup.in or reach me at 7087413515 for detailed conversation.